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By GODFRED ANTWI ISSER Conference Centre (ISSER New Building) WASTE AND SPOILAGE TECHNOLOGY OF THE 2000s: An Empirical Study.

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Presentation on theme: "By GODFRED ANTWI ISSER Conference Centre (ISSER New Building) WASTE AND SPOILAGE TECHNOLOGY OF THE 2000s: An Empirical Study."— Presentation transcript:

1 by GODFRED ANTWI ISSER Conference Centre (ISSER New Building) WASTE AND SPOILAGE TECHNOLOGY OF THE 2000s: An Empirical Study

2 Outline of the presentation The Problem Development of improved rice PBV Objective of study Methodology Findings Conclusions Recommendations The way forward References Acknowledgements 2

3 The Problem Post-harvest losses (waste and spoilage) constitute a major drain on food production and food security in Africa In Ghana, annual losses of cereals are between 20-30% which is mainly attributed to inadequate postharvest practices and technologies (MoFA, 2010). The Northern Region is a major producer of rice in Ghana (37%). Rice produced in the region is mostly parboiled due to harsh climatic conditions(high temperatures and low humidity) 3

4 The Problem cont’d  The widespread use of traditional rice-parboiling technology in Northern Ghana leads to poor quality of final rice which often does not meet consumers’ expectations 4

5 Development of improved rice PBV 5 iPBV(improved parboiling vessel) CPHP 2004 project(FRI and DFID) 2mm in thickness and has two chambers Parboil about max 100 kg of paddy Fuel savings of 30% - 50% Reduced drudgery in the parboiling process Vessel allows uniform heating (Tomlins et al., 2007).

6 Objective of the Study Assess the impact of an improved rice PBV adoption on household income in Northern region of Ghana. 6

7 Methodology 7 ObjectivesDescription of the ObjectiveMethod of analysis Objective oneDescribe the differences in the characteristics of adopters and non adopters households in the Northern region of Ghana. Descriptive statistics such as mean, minimum, maximum, standard deviation, percentages Objective TwoDetermine the factors that influence the adoption of iPBV technology in the Northern region of Ghana. Logit model (Green 2008; Baidu- Forson, 1999; Feder et al., 1985) Objective threeEstimate the impact of the adoption of iPBV technology on the household income in the Northern region of Ghana Propensity score matching(PSM) (Rosenbaum & Rubin, 1983; Becerril & Abdulai,2010;Dehejia & Wahba, 2002) Objective fourDetermine the major constraints faced by parboiling households in the Northern region Kendall’s coefficient of concordance

8 Variable descriptions of the logit model VariablesDescriptionMeasurementExpt. sign ADPTAdoption statusDummy(1= Adopted 0 = Otherwise ) Zugu Dagboni only Parboiler stays in Zugu Dagboni D(1= stays Zugu Dagboni 0 = Otherwise ) + Nyohini only Parboiler stays in Nyohini D(1= stays Nyohini 0=Otherwise ) - Nyankpala only Parboiler stays in Nyankpala D(1= stays Nyankpala 0=Otherw -/+ Education Educational level of respondent D(1= had formal education 0=Otherwise -/+ Age Age of respondent Continuous(years) -/+ Marital status D(1=married 0=otherwise) + Household size No of person being catered for Number of person + Member of group Member of parboiling organization D(1=member 0=otherwise) + Experience Years of rice processing experience Years + Production capacity Production capacity of the rice processor per month No of bags + Contact Contact with developmental organisation D(1= contact organisation 0=otherwise) + Household size Household size of the respondent Number of person + Hired labour Had used hired labour D(1= hired labour 0=otherwise) + Household income Per capita income(GHs) Continuous + 8

9 Study Area and Sampling Technique RegionDistrictCommunity# ProcessorsTotal Purposive Simple random (lottery method) Northern Tamale Metro Nyohini50 120 Zakariyeli20 Kpalsi30 Gbalahi20 Tolon Kumbungu Tolon40 120 Gbalahugu25 Nyankpala35 Zugu Dagboni20 TOTAL SAMPLE SIZE = 240 9

10 Results 10 Level of IPBV technology adoption

11 Results Objective one: 11 Adopters(n=80)Non-Adopters(n=160)Total(n=240) Variables Freq.% % % Age Less than 3625.031.339.024.46426.7 36-4527.033.865.040.69238.3 46-5520. Above 55 8.010.0 9.0 5.6177.1 Age_Mean 42.242.642.4 Gender Female 8033.316066.7240100 Marital status married 7492.514993.122392.9 Education No formal6682.512980.619581.3 Education_Mean 1.150.680.83 Household Size

12 Results Objective one: 12 Adopters(n=80)Non-Adopters(n=160)Total(n=240) Variables Freq.% % % Residential Status Native 6885.013685.020485 Migrant 1215.02415.03615 Other occupation Yes 5568.88150.613656.7 No 2531.37949.410443.3 Ethnicity Dagbomba 15697.57998.823597.9 Religion Muslim 7492.514087.521489.2 Experience Less than 11 33.012.57144.410443.5 11-20 38.047.56842.510644.2 21-30 8.010.01911.92711.2 Above 30 1.0 1.3 2 3 1.2 Experience_Mean 12.712.6

13 Results Objective one: 13 Adopters(n=80)Non-Adopters(n=160)Total(n=240) Variables Freq.% % % Purpose Consume &sale 6075.014288.820284.2 Source of water Pipe borne 6581.310968.117472.5 Quantity of paddy/month Less than 21 1519.05635.1 7129.6 21-30 2227.671.044.3 9338.8 31-40 30.037.526.016.4 3514.6 Above 40 13.016.47 4.4 4117.1 Quatity_Mean 32.326.328.3 Member of PBO Yes 7492.53924.411347.1 Credit Yes 4252.54528.18736.3 Contact Yes 7391.310666.312752.9 Aware of PBV technology Yes 801004830.012853.3

14 Results: Objective two T-Test : 14

15 Results: Obj 2 Logit results : 15

16 Results two Number of observations = 240 Psuedo R 2 = 0.62*** LR chi 2 (16) = 184.12 Prob > chi 2 = 0.0000 Log likelihood = -199.7286 *, ** and *** denotes 10%, 5% and 1% significance level respectively 16

17 Results Objective three and four: 17 Variable Matchi ng method TreatedControlsATT*ATU*ATE*S.E.T-stat Household income(GHS) NN2916.462294.69621.8519.5553.6225.262.76*** ATT= Average treatment effect on the treated ATU= Average treatment effects on the untreated ATE= Average Treatment Effect (overall)

18 Results Objective four; 18 Constraints AdoptersNon-Adopters Mean rank score RankMean rank scoreRank Lack of funds 2.32 1st 2.97 1st Expensive fuel (fire wood) 3.6 2nd 3.4 3rd Lack of equipment for parboiling 3.88 3rd 3.67 2nd Expensive/unreliable water 4.08 4th 3.93 5th Lack of drying area 4.5 5th 4.33 4th Distance to milling place is too far 5.21 6th 4.88 6th Low storage capacity 5.31 7th 5.36 7th Weak knowledge of drying operations 7.1 8th 7.47 8th Kendall's W a 0.335*** 0.34*** Chi-Square 187.686381.282

19 Findings All of respondents were female About 53% were aware of the existence of the technology. Education, Age,member of PBO, contact with developmental organisation, access to credit, targeted communities and high production capacity increases the probability of adopting the iPBV technology Price of paddy, having other occupation, household size,using hired labour and having a lot a experience reduces the probability of adopting iPBV technology 19

20 Findings Adopting the improved rice PBV technology increases the annual household income by 622 GHs The major constraints facing the parboilers were lack of funds, expensive fuel (fire wood) and lack of equipment for parboiling. Distance to milling place, Low storage capacity and weak knowledge of drying operations had minimal impact on their operations 20

21 Conclusion Improved rice PBV technology increases the household income for households who adopted the technology Constraints facing the parboilers were lack of funds, expensive fuel (fire wood) and lack of equipment for parboiling. 21

22 Recommendations Local artisans (such as welders, etc) and other stakeholders should pick up the technology and produce more iPBV with local resources ;this will even reduce the cost of the technology. Also stakeholders should encourage microfinance institutions to support rice parboilers with credit (since they are now creditworthy as a result of using the new technology which increases their incomes). Institution such as FRI, CSIR and Universities should develop alternate source of fuel (such as one the can use rice husk) to reduce the cost of fuel for processing rice. 22

23 The way forward In principle the new technology offer an increase in income to the parboilers but it is expensive; I. More developmental agencies should partner these women in other to acquire more of the technology for the women which has positive impact on their livelihood. II. Microfinance institutions should also be challenge to provide these women with credit at low interest to enable them to purchase this technology as to improve their income. 23

24 Some References A. Smith, J., & E. Todd, P. (2005). Does matching overcome LaLonde’s critique of nonexperimental estimators? Journal of Econometrics (Vol. 125, pp. 305–353). doi:10.1016/j.jeconom.2004.04.011 Abdulai, A., Owusu, V., & Bakang, J.-E. a. (2011). Adoption of safer irrigation technologies and cropping patterns: Evidence from Southern Ghana. Ecological Economics, 70(7), 1415–1423. doi:10.1016/j.ecolecon.2011.03.004 Abebaw, D., & Haile, M. G. (2013). The impact of cooperatives on agricultural technology adoption: Empirical evidence from Ethiopia. Food Policy, 38, 82–91. doi:10.1016/j.foodpol.2012.10.003 Diagne, M., Demont, M., & Diagne, A. (2009). Adoption and impact of an award winning post-harvest technology: The ASI rice thresher in the Senegal River Valley. Dehejia, R. H., & Wahba, S. (2002). Propensity Score-Matching Methods for Nonexperimental Causal Studies. Review of Economics and Statistics. doi:10.1162/003465302317331982 Dandedjrohoun, L., Diagne, A., & Biaou, G. (2012). Determinants of diffusion and adoption of improved technology for rice parboiling in Benin. Review of Agricultural and Environmental Studies, 93, 171– 191. Retrieved from 24

25 Thank you for your attention 25

26 Acknowledgements Dr. (Mrs.) Irene S. Egyir and Dr. John Baptist D. Jatoe AfricaRice African Development Bank(AfDB) Food Research Institute(FRI) The Economy of Ghana Network (EGN) 26

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